intent-cli-python 2.1.0

Semantic history for agent-driven development. Records what you did and why.

Intent

中文 | English

Semantic history for agent-driven development. Preserves how the product took shape and how work resumes across sessions and agents.

Why

Git records how code changes. But it doesn't record why you're on this path, what you decided along the way, or where you left off.

Intent adds that missing layer: semantic history — a small set of formal objects that preserve product formation history and survive context loss.

Development is moving from writing code to guiding agents and distilling decisions. The history layer should reflect that.

flowchart LR
  subgraph traditional["Traditional Coding"]
    direction TB
    H1["Human"]
    C1["Code"]
    H1 -->|"Git"| C1
  end
  subgraph agent["Agent Driven Development"]
    direction TB
    H2["Human"]
    AG["Agent"]
    C2["Code"]
    H2 -."❌ no semantic history".-> AG
    AG -->|"Git"| C2
  end
  subgraph withintent["Agent with Intent"]
    direction TB
    H3["Human"]
    AG2["Agent"]
    C3["Code"]
    H3 -->|"Intent"| AG2
    AG2 -->|"Git"| C3
  end
  traditional ~~~ agent ~~~ withintent

Three objects, one graph

Object	What it captures
Intent	A goal recognized from your query
Snap	A semantic checkpoint that captures what changed, what was learned, and later feedback
Decision	A long-lived constraint that spans multiple intents

Objects link automatically. Decisions auto-attach to every active intent; intents auto-attach to every active decision. Relationships are bidirectional and append-only.

flowchart LR
  D1["🔶 Decision 1"]
  D2["🔶 Decision 2"]

  subgraph Intent1["🎯 Intent 1"]
    direction LR
    S1["Snap 1"] --> S2["Snap 2"] --> S3["..."]
  end

  subgraph Intent2["🎯 Intent 2"]
    direction LR
    S4["Snap 1"] --> S5["Snap 2"] --> S6["..."]
  end

  D1 -- auto-attach --> Intent1
  D1 -- auto-attach --> Intent2
  D2 -- auto-attach --> Intent2

Install

pipx install intent-cli-python   # CLI
npx skills add dozybot001/Intent -g  # Agent skill

Requires Python 3.9+ and Git. The CLI provides the commands; the skill teaches the agent when to use them.

Tips: Because itt is a new command, agents are not trained on it yet. We recommend typing / at the start of each session, selecting the skill, and pressing Enter to enter the workflow.

IntHub

flowchart TB
  Hub["IntHub — Collaboration Layer"]
  Intent["Intent — Semantic History Layer"]
  Git["Git — Code History Layer"]
  Hub <--> Intent <--> Git

IntHub is the remote collaboration layer on top of Intent. The first path is IntHub Local — download from a GitHub release, then:

itt hub link --api-base-url http://127.0.0.1:7210
itt hub sync

Open http://127.0.0.1:7210 in the browser.

Docs

• Vision — why semantic history matters
• CLI Design — object model, commands, JSON contract
• Roadmap — phase plan
• Dogfooding — cross-agent case study
• IntHub Local — run a local IntHub instance

License

MIT